How volatility evolves over time

How illiquidity evolves over time

{name} Model Equation

How returns affect tomorrow's volatility

How returns affect tomorrow's illiquidity

Spline Coefficients

Value at Risk (VaR) estimates the maximum loss at a given confidence level. Expected Shortfall (ES) estimates the average loss beyond VaR.

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Param	Value	t-stat
ωconst	7.7898	3.62***
αARCH	0.3992	5.89***
βGARCH	0.5964	8.77***

γ₁	-6.9371	-5.14***
γ₂	23.4221	10.44***
γ₃	-31.6320	-16.63***
γ₄	23.3383	15.64***
γ₅	-9.4690	-5.18***
γ₆	-3.6589	-1.53
γ₇	7.6395	2.14**
γ₈	-0.2739	-0.06
γ₉	-7.4117	-1.53
γ₁₀	23.2626	5.78***

Parameter	Value	t-statistic
ω const Unconditional variance weight	7.7898	3.62***
α ARCH Response to squared shocks	0.3992	5.89***
β GARCH Volatility persistence	0.5964	8.77***

γ₁	-6.9371	-5.14***
γ₂	23.4221	10.44***
γ₃	-31.6320	-16.63***
γ₄	23.3383	15.64***
γ₅	-9.4690	-5.18***
γ₆	-3.6589	-1.53
γ₇	7.6395	2.14**
γ₈	-0.2739	-0.06
γ₉	-7.4117	-1.53
γ₁₀	23.2626	5.78***

V-Lab

Nouveau Global Ventures Ltd Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Nouveau Global Ventures Ltd Analyses